About the Book

Showcasing the beauty of protein structures, Structural Bioinformatics: An Algorithmic Approach illustrates how to apply key algorithms to solve a range of biological issues.

Following some introductory material in the first few chapters, the text solves the longest common subsequence problem using dynamic programming and explains the science models for the Nussinov and MFOLD algorithms. It then reviews sequence alignment, along with the basic mathematical calculations needed for measuring the geometric properties of macromolecules. After looking at how coordinate transformations facilitate the translation and rotation of molecules in 3-D space, the author introduces structural comparison techniques, superposition algorithms, and algorithms that compare relationships within a protein. The final chapter explores how regression and classification are becoming more useful in protein analysis and drug design.

Connecting biology, mathematics, and computer science, this practical text presents various bioinformatics topics and problems within a scientific methodology that emphasizes nature (the source of empirical observations), science (the mathematical modeling of the natural process), and computation (the science of calculating predictions and mathematical objects based on mathematical models).

Features:

• Emphasizes a methodology that uses mathematical models to act as links between structural biology and computational algorithms
• Gives many examples of dynamic programming applications, including RNA secondary structure prediction and protein sequence alignment
• Presents the basic mathematical techniques underlying core algorithms in structural bioinformatics
• Reviews necessary mathematics, such as linear algebra, in the appendices
• Includes problems throughout, exercises at the end of each chapter, and a 12-page color insert
• Entices the reader to see that protein structure can produce symmetry and beauty as well as biological function